run("Devices/Elements")

def _create_tables(paths, stream_value, data_type, shape):
    root = paths["root"]
    create_dataset(paths["image"], data_type, dimensions = [images, shape[0], shape[1]])
    create_dataset(paths["pid"], 'l', dimensions = [images])
    create_dataset(paths["timestamp_str"], 's', dimensions = [images])
    for id in stream_value.identifiers:
        val = stream_value.getValue(id)
        if id == "image":
            pass
        elif id == "processing_parameters":                                                                     
            val = json.loads(val)                
            for key in val.keys():    
                   set_attribute(paths["image"], key, "" if val[key] is None else val[key] )               
        elif isinstance(val, PyArray):
            create_dataset(root + id, 'd', dimensions = [images, len(val)])                                
        elif isinstance(val, PyLong):
            create_dataset(root + id, 'l', dimensions = [images])                
        elif isinstance(val, PyFloat):
            create_dataset(root + id, 'd', dimensions = [images])                
        else:   
            print "Unmanaged stream type: ", val, type(val)
            pass
    

def _append_frame(paths, stream_value, index, data_type, shape):
    print "Saving frame :", index
    #append_dataset(paths["image"], data, index, type = data_type)    
    root = paths["root"]
    append_dataset(paths["image"], stream_value.getValue("image"),[index,0,0], type = data_type,  shape=[1, shape[0], shape[1]])      
    append_dataset(paths["pid"], stream_value.getPulseId(), index)
    append_dataset(paths["timestamp_str"], datetime.datetime.fromtimestamp(stream_value.timestampNanos/1e9).strftime('%Y-%m-%d %H:%M:%S'), index)   

    for id in stream_value.identifiers:
        try:
            val = stream_value.getValue(id)
            if id == "image":
                pass
            elif isinstance(val, PyArray):
                append_dataset(root + id, val, index)
            elif isinstance(val, PyLong):
                append_dataset(root + id, int(val), index)
            elif isinstance(val, PyFloat):
                append_dataset(root + id, float(val), index)
            else:      
                pass
        except:
            print id, val
            traceback.print_exc()
       
    print "Saved frame: ", index


def _write_metadata(paths, camera_name, shared = False, images = 1, interval = -1):
    root = paths["root"]    
    set_attribute(root, "Name", camera_name)
    set_attribute(root, "Shared", shared)
    set_attribute(root, "Images", images)
    set_attribute(root, "Interval", interval)
    cam_type = get_camera_type(camera_name)
    set_attribute(root, "Type", cam_type)
    if cam_type=="ELECTRONS":
        set_attribute(root, "Screen", caget(camera_name + (":POSITION" if (camera_name.startswith("DSRM")) else ":GET_SCREEN1_POS"), 's'))
        set_attribute(root, "Filter", caget(camera_name + ":GET_FILTER", 's'))

    
def save_camera_data(server, camera_name, shared = False, root = "/", images = 1, interval = -1, parallel = True, pause = False):
    stream_value = server.stream.take()
    if stream_value is None:
        server.waitNext(10000)
        stream_value = server.stream.take()
    if not root.endswith('/'):
        root = root + "/"
    paths = {"root": root, "image":root+"image", "pid":root+"/pulse_id", "timestamp_str":root+"/timestamp_str"}    
    shape = [stream_value.getValue("height"),stream_value.getValue("width")]
    data_type = stream_value.getValue("image").typecode    
    
    tasks = []  
    if pause:
        server.paused = True
    try:    
        for i in range(images):    
            if i==0:                                
                _create_tables(paths, stream_value, data_type, shape)
                _write_metadata(paths, camera_name, shared, images, interval)
        
            start = time.time()
            stream_value = server.stream.take()
            if parallel:                   
                tasks.extend( fork((_append_frame,(paths, stream_value, i, data_type, shape)),) )
            else:
                _append_frame(paths, stream_value, i, data_type, shape)
                
            if i< (images-1):
                if interval<=0:
                    server.stream.waitCacheChange(10000)                            
                else:
                    sleep_time = float(interval)/1000.0 - (time.time()-start)
                    time.sleep(max(sleep_time,0))    
    finally:      
        if pause:
            server.paused = False
        pass
        
    print "Waiting finish persisting..."
    join(tasks)
    print "Done"